Comments on Why Generalized BP Serves So Remarkably in 2-D Channels

Comments on Why Generalized BP Serves So Remarkably in 2-D Channels

Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Shental, O., Shental, N., Shamai, S., Kanter, I., Weiss, A.J., Weiss, Y.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
AWGN
Belief propagation
Gaussian channels
Graphical models
Information rates
Interference
Message passing
Nearest neighbor searches
Probability
Two dimensional displays
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.
DOI:10.1109/ITA.2007.4357604